How Trustworthy Are AI Outputs?

AI-powered tools are everywhere—to enhance workflows, analyze data, generate documents, answer customer questions and more. They unlock all kinds of opportunities to slash operational expenses and fuel growth. But can you trust them?

While AI dramatically speeds up workflows and informs decisions, using it without proper checks comes with some serious risks. Let’s talk about the real deal with AI outputs—what they are, how they work and practical steps for using them effectively and responsibly.

The Promise of AI for SMBs

Let’s face it: The changing economic landscape means most of us need to do more with less. AI tools can boost your team’s productivity, take over mind-numbing repetitive tasks and even improve your client experience—all without adding headcount.

For example …

Imagine your accounting team analyzing financial documents in seconds instead of hours. Or your legal department speeding through research that used to take days. From real estate to healthcare to finance, the opportunities for fast, scalable intelligence touch virtually every industry. And unlike previous waves of enterprise tech only big companies could afford, today’s AI tools are accessible, affordable and increasingly user-friendly—meaning businesses of all sizes can put them to work.

No wonder nearly 80% of SMBs say AI will be a game changer for their companies. However, there is a catch.

AI doesn’t always get things right.

The Problem with AI Outputs

Any professional who’s used AI-powered tools understands the dangers of blindly accepting outputs. You prompt the app with data, it spits back an analysis—but how the tool arrives at its conclusions is often a mystery.

And sometimes, it’s flat-out wrong.

One analysis found AI chatbots answer as much as 60% of inquiries incorrectly. Another revealed major biases and potentially harmful or questionable content in both image and text outputs. For these reasons, many knowledge workers don’t trust the data that trains AI—in fact, 68% are still hesitant to adopt it.

The culprit? A phenomenon known as “AI hallucination.” This happens when an AI-powered tool produces an output—such as a statement, citation or statistic—that’s entirely made up. It may sound confident while being dangerously wrong.

A recent AI fact checking accuracy study helps explain why and how this happens:

• Not all datasets are accurate: Popular tools like ChatGPT are trained on vast datasets from the internet, which include both accurate and inaccurate information. As a result, these models can generate responses that sound plausible but are factually incorrect.
• Fact-checking tools vary in quality: Even the most accurate tools aren’t infallible, underscoring the importance of cross-verifying AI-generated information with reliable sources.
• Training data may include biased or outdated information: AI models learn from the data they’re trained on, which may contain misinformation. Without proper curation, these issues can be perpetuated in AI outputs.

Bottom line: While many AI tools sound trustworthy, they don’t always get the details right. In the world of content creation, this might lead to embarrassing situations. But in heavily-regulated legal, financial or healthcare contexts? It can be catastrophic.

So what can you do about it?

How to Use AI Safely and Effectively

Yes, AI tools come with risks. But that doesn’t mean you should avoid them altogether. In fact, the opposite is true—understanding these limitations allows you to leverage AI in the most powerful ways possible. Here are several ways to do just that.

1. Use AI for Drafts, Not Decisions

Let AI handle the first draft of a document or report, but keep the final signoff in human hands. If an AI-generated email feels “off,” it probably is.

2. Train Your Team to Question AI Outputs

Approaching AI-generated information critically is crucial. Validate it against up-to-date and unbiased sources. Create a culture of healthy skepticism where fact-checking becomes second nature before anything gets approved.

3. Set Clear AI Usage Policies

Develop internal guidelines about how and when AI can be used, making it easier for your team to comply with relevant regulations. Establish requirements for human reviews of AI outputs before they’re published or sent, especially when dealing with sensitive data or client communication.

4. Choose Platforms That Prioritize Data Security and Compliance

Not all AI tools are created equal. Look for ones that offer transparent practices, encryption and audit trails. Better yet, adopt tools built with security and compliance in mind—especially if you work in a heavily regulated industry.

Moving Forward with AI

There’s no question AI delivers huge benefits to SMBs, from faster turnaround times to leaner operations. But treating it like a foolproof oracle is a recipe for errors, not efficiency. The smartest approach? Use AI as a powerful assistant, not as your sole decision maker.

For a deeper look at how SMBs can adopt AI confidently—from choosing tools to achieving compliance—download our free best practices guide: The No-Nonsense SMB Guide to AI.